IoT Data as a Service (IoTDaaS) Market Outlook and Forecasts 2016 - 2021




Published: November 2016   Pages: 102
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Overview:

The Internet of Things (IoT) will bring a whole new meaning to the term Infonomics, which pertains to the economic significance of information. IoT Data as a Service (IoTDaaS) offers convenient and cost effective solutions to enterprises of various sizes and domain. IoTDaaS constitutes retrieving, storing and analyzing information and provide customer either of the three or integrated service package depending on the budget and the requirement.

Acquiring (capturing and/or licensing), storing, processing, and distributing IoT Data to become a $15B USD business by 2021

Mind Commerce evaluates leading technologies and tools under development, maps benefits to market needs, identifies key solutions, and forecasts market opportunities and demands. This research provides comprehensive analysis of the IoT Data as a Service marketplace. The report includes comprehensive forecasts for the period 2016 – 2021.

Readers of this report will also be interested in the more comprehensive report entitled: IoT Data Management and Analytics Market Outlook & Forecasts 2016 - 2021

Target Audience:

  • Network service providers
  • Systems integration companies
  • IoT and wireless device manufacturers
  • Network and device security companies
  • Data management and analytics companies

Table of Contents:

1 Introduction
1.1 Research Background
1.2 Research Scope
1.3 Target Audience
2 Executive Summary
3 Overview
3.1 IoT Data in the Emerging Data Economy
3.1.1 IoT Data Strategy
3.1.2 IoT and the Analytics of Things
3.1.3 Specific Strategic Considerations
3.1.3.1 Focus on Data Tiers
3.1.3.2 Maintain a Value-based Approach
3.1.3.3 Foster an Open Development Environment
3.2 Understanding IoT Data
3.2.1 IoT Data vs. other Unstructured Data
3.2.2 Key IoT Data Characteristics
3.2.2.1 IoT Data is Real Time
3.2.2.2 Massive Volumes of IoT Data
3.2.2.3 IoT Data Generates Useful Insights
3.3 IoT Data Management Operations
3.3.1 Basic Data Implementation and Operational Challenges
3.3.1.1 IoT Data Scalability
3.3.1.2 IoT Data Integration
3.3.2 Data Management and Processing Raw Data
3.3.3 Centralized Storage and Decentralized Processing
3.3.4 Accessing and Exchanging IoT Data via APIs
3.3.5 Data Security and Personal Information Privacy
3.4 Monetizing IoT Data and Analytics
3.4.1 IoT Data vs. IoT Data Analytics
3.4.1.1 IoT Data
3.4.1.2 IoT Data Analytics
3.4.2 Key IoT Data Management Monetization Issues
3.4.2.1 IoT Data Ownership
3.4.2.2 IoT Data Care of Custody
3.4.3 Direct vs. Indirect Monetization
3.4.4 Internal vs. External Enterprise IoT Data Monetization
3.4.4.1 Enterprise Data and Analytics: Internal Monetization
3.4.4.2 Enterprise Data and Analytics: External Monetization
3.4.5 Public Data Monetization
3.4.6 Hybrid IoT Monetization
3.4.7 Emerging IoT Data Management and Analytics Marketplace
3.4.7.1 IoT Data as a Service
3.4.7.2 IoT Data Analytics as a Service
3.4.7.3 Decisions as a Service
3.5 Related Monetization Areas
3.5.1 IoT OSS and BSS
3.5.1.1 IoT Operational Support Systems
3.5.1.2 IoT Billing Support Systems
3.5.2 IoT Mediation and Orchestration
3.5.2.1 IoT Mediation and Orchestration Functionality
3.5.2.1.1 IoT Mediation and Orchestration: Virtualization
3.5.2.1.2 IoT Mediation and Orchestration: Identity Management
3.5.2.1.3 Emerging Technologies for IoT Mediation and Orchestration
3.5.2.2 IoT Mediation and Orchestration in Support of Industry Verticals
3.5.2.3 Communication Service Provider Role in IoT Mediation and Orchestration Ecosystem
3.5.2.4 IoT Mediation and Orchestration Roadmap
3.6 Market Outlook for IoT Data Analytics
3.6.1 IoT Data Management is a Ubiquitous Opportunity across Enterprise
3.6.2 IoT Data becomes a Big Revenue Opportunity by 2021
3.6.3 Organizations increasing Adopt Predictive Analytics with IoT Data
3.6.4 Real-time Streaming IoT Data Analytics becoming a Substantial Business Opportunity
3.6.5 Intelligent Strategy and Smart Investment in IoT Data Analytics
3.6.6 IoT Data to Produce Substantial Operational Savings and Generate New Business
3.6.7 Tools Designed Specifically for IoT Data Management and Analytics
3.6.8 IoT Data Management and Analytics Roadmap 2016 to 2025
3.6.8.1 IoT Data Landscape from 2016 to 2018
3.6.8.2 IoT Data Landscape from 2019 to 2020
3.6.8.3 IoT Data Landscape from 2021 to 2025
4 IoT Data as a Service Forecasts 2016 - 2021
4.1 Global IoT Data as a Service 2016 - 2021
4.2 Regional IoT Data as a Service 2016 - 2021
4.3 IoT Data as a Service by Industry Vertical 2016 – 2021
5 Conclusions and Recommendations

Figures

Figure 1: IT and OT IoT Data Merge
Figure 2: IoT Data Strategy impacts Architecture
Figure 3: A Vision of IoT Data by 2021
Figure 4: IoT Data vs. Non-IoT Unstructured Data
Figure 5: IoT Data Processing Flow
Figure 6: Distributed IoT Data Architecture
Figure 7: IoT Data Not Stored Only
Figure 8: Real-time IoT Data Management and Analytics
Figure 9: APIs enable IoT Data Access and Exchange
Figure 10: Security in IoT Data Architecture
Figure 11: IoT Data Care of Custody
Figure 12: Direct vs. Indirect IoT Data Monetization
Figure 13: Internal vs. External IoT Data Monetization
Figure 14: Merging IoT Data Sources – Hybrid Data
Figure 15: IoT Data Exchange Marketplace
Figure 16: IoT Mediation Architecture
Figure 17: IoT Identity Database Functionality
Figure 18: IoT Permissions Database
Figure 19: IoT Permissions Hierarchy
Figure 20: IoT Device Discovery and Alerting
Figure 21: IoT Device Discovery Dashboard
Figure 22: Smartphone Alert of Blocked IoT Connection Attempt
Figure 23: Smart Watch Alert of Blocked IoT Connection Attempt
Figure 24: IoT Mediation and Virtual Control of Real Objects
Figure 25: IoT Mediation in Industry Verticals
Figure 26: Phase One: Limited IoT Data Sharing without Formalized Mediation
Figure 27: Phase Two: IoT Data Sharing between Limited Industries
Figure 28: Phase Three: Broadly shared IoT Data across Industries and between Competitors
Figure 29: Inclusion of Predictive Models in Streaming IoT Data Analytics
Figure 30: Streaming IoT Data Sources Compared
Figure 31: Comparison of IoT Data Analytics Investment Focus
Figure 32: IoT Data Analytics Technology and Tool Choice in Enterprise
Figure 33: IoT Data Operational Savings and New Revenue Opportunities
Figure 34: IoT Data Management and Analytics Roadmap 2016 to 2025
Figure 35: IoT Data-as-a-Service Market 2016 – 2021
Figure 36: IoT Data-as-a-Service Revenue by Region 2016 – 2021
Figure 37: IoT Data-as-a-Service Revenue by Industry Sector 2016 – 2021
Figure 38: IoT Technology and Solutions Stack

Tables

Table 1: IoT Data as a Service Market 2016 – 2021
Table 2: IoT Data as a Service Revenue by Region 2016 – 2021
Table 3: IoT Data as a Service Revenue by Industry Vertical 2016 – 2021


Categories



M2M and IoT

Data and Analytics

Strategy
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